Anomaly Detection On Mnist
Metriken
ROC AUC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | ROC AUC | Paper Title | Repository |
---|---|---|---|
IGD (pre-trained ImageNet) | 99.27 | Deep One-Class Classification via Interpolated Gaussian Descriptor | |
IGD (scratch) | 98.69 | Deep One-Class Classification via Interpolated Gaussian Descriptor | |
LIS-AE | 97.68 | Latent-Insensitive autoencoders for Anomaly Detection | - |
DASVDD | 97.7 | DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection | |
GAN-based Anomaly Detection in Imbalance Problems | 99.7 | GAN-based Anomaly Detection in Imbalance Problems | - |
P-KDGAN | 97.25 | P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection | - |
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